Abrehet et al. 2014
Accepted: 16/7/014 by Ecohydrology & Hydrobiology (Elsevier)
Spatial and seasonal variation in the macro-invertebrates and
physico-chemical parameters of the Enfranz River, Lake Tana
Sub-Basin (Ethiopia)
Abrehet Kahsay Mehari1, Ayalew Wondie2, Minwyelet Mingist1 and Jacobus
Vijverberg3*
1
Fisheries, Wetlands and Wildlife Management Program, Bahir Dar University, PO Box 79,
Bahir Dar, Ethiopia
2
Biology Program, Bahir Dar University, PO Box 79, Bahir Dar, Ethiopia
3
Department of Aquatic Ecology, Netherlands Institute of Ecology (NIOO-KNAW),
Droevendaalsesteeg 10, 6708 PB Wageningen, The Netherlands
*)
Corresponding author: e-mail: k_vijverberg@yahoo.co.uk
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Abstract
The main objective of the study was to assess the water quality of the Enfranz River by
studying the distribution of macro-invertebrate taxa on the longitudinal gradient of the river.
The macro-invertebrate community of the Enfranz River, located northwest of Bahir Dar city
in the southern part of Lake Tana watershed, was studied to family taxonomic level in wet and
dry seasons from August 2010 to May 2011. The river was sampled along its whole length at
four sites from headwaters until its outflow in Lake Tana. A total of 15,286 macroinvertebrate individuals belonging to 35 families and 2 higher taxa were collected. The
Shannon-Wiener diversity Index, the Hilsenhoff family-level biotic index, and three macroinvertebrate metrics, were measured and related to five physico-chemical parameters. Macroinvertebrate diversity and biotic indices, and community metrics differed significantly among
sampling sites (p < 0.05), diversity being higher at the headwaters. Spearman’s correlation
coefficients showed that dissolved oxygen was significantly correlated with the macroinvertebrate diversity and biotic indices, and all three macro-invertebrate metrics (p < 0.05).
Diversity index, percent Ephemeroptera and percent Trichoptera were positively correlated to
dissolved oxygen, whereas the biotic index and percent dipterans showed negative
correlations. Furthermore, percent Ephemeroptera was negatively correlated with conductivity
(p<0.05) and diversity was negatively related to total dissolved solids and conductivity. We
conclude that downstream, the river is severely affected by land use of the people living along
the river.
Key words: Benthic macroinvertebrates, Biodiversity, Biomonitoring, Bioindicators,
Effects of land use, Water quality, Water quality management.
Running headline: Spatial variation in macro-invertebrates
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1. Introduction
Freshwater ecosystems have been altered by human disturbances such as agriculture, urban
development, impoundment, channelization, mining, forest fire suppression, road construction
and species introductions (LaBonte et al., 2001). All of these have led to severe degradation and
loss of biodiversity (Vinson and Hawking, 1998) and as a result these ecosystems have become
the most endangered ecosystems on the planet (Dudgeon et al., 2006). While many taxa
contribute to biodiversity in freshwater ecosystems, aquatic macro-invertebrates play a central
ecological role in many running water ecosystems (Boulton, 2003) and are among the most
ubiquitous and diverse organisms in freshwaters (Strayer, 2006). Aquatic macro-invertebrates
form an important component of the trophic structure of freshwater ecosystems since they play
an important role in the food webs (e.g., Grubh and Mitsch 2004) and stimulate nutrient cycling
by reducing the size of organic particles (Callisto et al., 2001).
Macro-invertebrates are often used as biomonitoring tools (Dallas and Mosepele, 2007).
Biomonitoring is based on the principle that organisms are the ultimate indicators of the health of
the environment they are within (USEPA, 2002). Biomonitoring has the advantage that it can
detect cumulative physical, chemical and biological impacts of adverse activities to an aquatic
system. Aquatic macro-invertebrates are often preferred for biomonitoring because of the
following three reasons: firstly, they are not very mobile and therefore they are representative of
the area from which they are collected, secondly they have relatively short life cycles and
therefore can reflect environmental changes quickly through changes in their community
composition and finally they respond to pollutants in both water column and sediments (Reece
and Richardson, 2000).
In Africa there is an increasing trend to use benthic macro-invertebrate
communities in rivers and streams as indicators of environmental quality (e.g.,
Shivoga, 2001; Dickens and Graham, 2002; Ndaruga et al., 2004; Kibichii et al., 2007;
Kasangaki et al., 2008; Masese et al., 2009b; Minaya et al., 2013). However, to best
characterize ecological conditions of rivers and streams, the development of a single index from
biological and environmental variables is preferred (Masese et al., 2013). This approach involves
integration of a number of structural and functional attributes of the macro-benthic community,
termed ‘metrics’, into a composite index with the rating of each metric based on
3
quantitative expectations (based on comparisons with reference conditions) of what
represents high biotic integrity. The employment of the multimetric Index of Biotic Integrity
(IBI) is rapid and cost effective (Masese et al., 2009a). Besides Europe and the United
States, the use of a n Index of Biotic Integrity (IBI) to monitor streams and rivers to
assess the degree of ecosystem degradation has not been much used (Masese et al.,
2013). To date, there are only a few African studies available, most studies are from
South Africa where they developed a fast s coring system (e.g., Dickens a n d Graham
2002) and a few studies from NE Africa (Sitotaw, 2006, Kobingi et al., 2009; Masese
et al. 2009a; Raburu et al. 2009a, b; Aura et al., 2010).
In Ethiopia studies on benthic macroinvertebrates in streams and rivers are sparse. Hynes
et al. (1989) and Hailu and Legesse (1997) were the first to study macro-invertebrates and to use
them to assess the pollution status of Ethiopian streams. Harrison and Hynes (1988) described in
detail the community composition of benthic macro-invertebrates of mountain streams belonging
to 7 different rivers systems. Their interest was mainly on the biogeography of Afrotropical
mountain stream fauna. Sitotaw (2006) was the first in Ethiopia to assess a Benthic Index of
Biotic Integrity in his study on nine Ethiopian rivers. He concluded that extensive agricultural
activities and industrial and urban land-use were the most important threatening factors to river
ecosystems in Ethiopia. Beyene et al. (2009) assessed the relative performance of diatoms and
macro-invertebrates to measure municipal and industrial impacts on the biological integrity of
three major rivers flowing through Addis Ababa. Ambelu et al. (2010) collected data on macroinvertebrates and physico–chemical characteristics in the Gilgel Gibe River basin in SouthWestern Ethiopia to developed models predicting macro-invertebrate metrics, which could be
used for river management.
The present study is the first study on macro-invertebrates in one of the ca. 47 rivers
flowing into Lake Tana, Ethiopia’s largest lake. The purpose of this study on Enfranz River was
three fold: (1) to assess the spatial and seasonal variation of physico-chemical parameters and
macro-invertebrate diversity and other community metrics over a river continuum from
headwaters until its outflow into Lake Tana, (2) to assess the spatial and seasonal variation in
water quality over this river continuum, and (3) to develop a monitoring system on which
guidelines for conservation and management could be based.
4
2. Materials and methods
2.1. Study area and land-use
The Enfranz River is situated northwest of Bahir Dar city and the upper stream of the
river is rich with a number of springs. These head springs are the source of drinking water for the
city. It drains to southwest of Lake Tana and its catchment area is ca. 198 km2 (Kidan 2010). The
main water source of the Enfranz River, besides surface water, is groundwater. This water is
directly pumped to the people in the city from wells drilled near the river (Kassahun, 2008). The
total population of Bahir Dar was in 2007 ca. 220,000 inhabitants and has a population growth
rate of 6.6 % per year (CSA, 2007), which is more than twice as high as the average population
growth rate in Ethiopia.
The climate of the Enfranz River area is characterized by rainy season during JulySeptember, dry season during December–April, pre-rainy season during May–June and postrainy season during October–November. The wetlands in the Enfranz River watershed occupy an
area of ca. 2500 ha and are inhabited by ca. 24000 people. The wetlands are used for extensive
grazing and agriculture by subsistence farmers mainly during the dry season (December-April).
Most of the land (ca. 80%) is used for grazing of cattle and ca. 10% is used for extensive
agriculture mainly chat (Cathi edulis) and the culture of flowers (Fig. 1). The remaining land is
occupied by shrubs (ca. 10%) which are dominated by Aloe spp. and human settlements (<
5%).The riparian vegetation is diverse and consists of about 27 species of shrubs of which three
species are endemic to Ethiopia (Erythrina brucei, Mellitia ferruguina and Acanthus senni)
(Kidan, 2010). Trees are sparse along the stream. Most trees, predominantly Scysigium
guineense (dok’ma), Ficus spp. and Euphorbia spp., are present around station E3.
2.2. Sampling
This study was conducted in wet and dry seasons of 2010-2011. Samples for both physicochemical parameters and macro-invertebrates were collected in August and October 2010 and
January and May 2011. Four sampling sites along the longitudinal river gradient were selected
and the sites were designated as E1 to E4. In total 16 pooled samples were taken. Sampling sites
5
ranged from headwaters (E1) to the mouth of the river (E4), where the water flows into Lake
Tana. The detailed description of the sampling sites is presented in Fig. 1 and Table I.
Physico-chemical parameters
Samples for physico-chemical parameters were taken at the same location and almost
simultaneously with the samples for macro-invertebrates. Water temperature, dissolved oxygen
(DO), pH, total dissolved solids (TDS) and conductivity were measured in situ using electronic
measure equipment. Conductivity, pH, TDS and temperature were measured with a SyberScan
PC 300 (Eutech Instruments), whereas dissolved oxygen was measured with a SyberScan DO
300 (Eutech Instruments).
Macro-invertebrates
Quantitative sampling was carried out based on the rapid bio-assessment protocols that are used
for rivers and wadeable streams (Barbour et al. 1999). Samples were taken using dip net with
mesh size of 500 µm (mouth 50 x 30 cm, 60 cm deep, handle 132 cm). In the field, the collected
material was sieved through 500 µm and 250 µm mesh sieves and put into collection bottles. The
sampling effort at each site was 30 minutes. Within a site two riffles and two pools were
sampled, but macro-invertebrates were pooled so as to obtain a single sample from each site. All
samples were preserved with 70% ethanol until laboratory analyses and counting. All the
organisms in the sample were counted and identified to the lowest possible taxonomic level
(family level) using a dissecting microscope and standard keys (Edmondson, 1959; Merrit and
Cummins 1988; Jessup et al., 1999; Gooderham and Tysrlin, 2002; Bouchard, 2004). There were
no keys available to the Ethiopian fauna, but the standard keys used made it possible to classify
the macro-fauna specimens to the family level without loss of accuracy.
2.3. Data Analysis
Descriptive statistics were used to analyze physico-chemical data. For the macro-invertebrate
communities two indices were calculated for each site and each sampling date. The ShannonWiener Diversity Index (H′) is a diversity index that incorporates richness and evenness. A high
H′ indicates a good water quality. H′ was calculated as follows:
6
H′ = - ∑ (Pi ln [Pi])
Eqn 1
Where: Pi is the relative abundance (ni/N) of family i, ni = number of individuals in family i and
N = total number of individuals in all families. H′ is ranging from 0 for a community with a
single family, to over 7 for a very diverse community. An H’ value of less than 1 indicates highly
polluted, 1-3 moderately polluted, and greater than 4 unpolluted water bodies (Wilhm and
Dorris, 1968).
The Hilsenhoff Family-level Biotic Index (HFBI was not designed for tropical rivers, but
there are no limitations for use in Ethiopian tropical streams because the same families are
present in tropical and temperate rivers. It is calculated by multiplying the number of individuals
of each family by an assigned tolerance value for that family. Assigned tolerance values range
from 0 to 10 for families and increase as water quality decreases (Hilsenhoff, 1988; Bode et al.,
1996). This Index was calculated as follows:
HFBI = Σ [(TVi) (ni)] ⁄ N …………………………………..Eqn 2
Where: TVi is tolerance value for family i, ni is the number of individuals in family i and N is the
total number of individuals in the sample collection. High HFBI community values are an
indication of organic pollution, while low values indicate good water quality.
Excel spreadsheets and statistical software (SPSS version 16) were used for the statistical
analysis. Kruskal-Wallis analysis by ranks was used to evaluate differences in physico-chemical
data and macro-invertebrate metrics among the sampling sites, whereas differences between
seasons were assessed with the Mann-Whitney U test. Spearman’s rank correlation coefficients
were used to determine the relationships between physico-chemical parameters and diversity and
biotic indices and macro-invertebrate metrics.
3. Results
3.1. Physico-chemical Parameters
The mean values (mean + SE) of dissolved oxygen (DO) ranged from 3.27 + 0.23 mg l-1 at the
mouth of the river (E4) to 6.08 + 0.14 mg l-1 in the headwaters (E1) (Table II). The mean value
of dissolved oxygen showed significant variation among sampling sites (p<0.05), the value at E1
being significantly higher than at the other sites. The mean values of dissolved oxygen in wet
7
and dry season were similar and not significantly different ( p>0.05). The percent oxygen
saturation values at ambient temperatures showed the same trend, high at the headwaters (67%)
and low at the mouth of the river (37%). All saturation values were well below 100%.
Temperature did not differ significantly among sampling sites (p> 0.05, range: 18.1-29.1
o
C) and seasons (p>0.05, range for wet season: 18.1-23.4 oC, range for dry season: 18.9-29.1 oC).
The mean value of total dissolved solids (TDS) along the study sites ranged from 82.78 + 10.51
ppm at E2 to 146.5 + 20.04 ppm at E4, while its value in wet and dry season was 92.45 + 11.41
ppm and 117.9 + 12.62 ppm, respectively (Table II). Conductivity followed the same trend.
There was significant variation among sampling sites (p<0.05). TDS values at E4 were
significantly higher than the values at E2 and E3. However, this was not the case for
conductivity. Although conductivity values at E4 were significant higher than at E2, differences
between E4 and E3 were not significant. In both cases, differences among seasons were not
significant (p>0.05). The grand mean value of pH was 7.1 (Table II). Values did not differ
significantly among sampling sites (p>0.05) and seasons (p>0.05).
3.2. Macro-invertebrates
Taxa
A total of 15,286 macro-invertebrate individuals belonging to 35 families and 2 higher taxa were
collected from 4 sites during the survey work (Fig. 2, Table III). The total number of individuals
present at each site ranged from 2,690 at E1 to 6,473 at E4, and 6,512 and 8,774 during wet and
dry seasons, respectively. Libellulidae was the most abundant family (2,540 individuals),
followed by Chironomidae (1,747 individuals), Belostomatidae (1,135 individuals),
Coenagrionidae (1,106 individuals), Culicidae (678 individuals), then Corixidae (675
individuals).
We reviewed how many families (taxa) were represented in each of four sampling sites.
At consecutive sampling sites (E1, E2, E3, E4) 30, 28, 22 and 21 taxa were represented, but
changes resulted not only from loss of individual taxa. At E2 two ephemeropteran families, 4
trichopteran families and 1 family belonging to Odonata were lacking as compared to E1, but 1
hemipteran family, 3 molluscan families and 1 arachnides family appeared. At E3 one
trichopteran family, 1 Odonata family, 1 Coleoptera family, 3 molluscan families, 1 arachnides
8
family and 1 Hydracarina family were lacking as compared to E2, but 1 molluscan family, 1
arachnides family and 1 Hirudinea family appeared. At E4 one ephemeropteran family, 2
hemipteran families and 1 Coleoptera family were lacking as compared to E3, but 1 molluscan
family, 1 arachnides family and 1 Hydracarina family appeared.
The mean proportions of ephemeropterans varied between 0.12% and 23.59%. The
lowest value was observed at E4 and the highest value at E1, differences between downstream
stations (E3, E4) and stations upstream (E1, E2) were large (Table IV). Differences among
sampling sites were significant (p<0.05). The proportions at E4 were significantly lower than
those at sites 1, 2 and 3. In contrast, the difference between seasons were small and not
significant (p>0.05).
The mean proportions of trichopterans ranged from 0.00% at E4 and E3 to 12.59% at E1
(Table IV). Differences between downstream stations (E3, E4) and stations upstream (E1, E2)
were large. Differences among sampling sites were significant (p<0.05). We did not observe any
trichopterans at E3 and E4. The difference between seasons was relatively large (Table IV) and
significant (p<0.05).The mean proportions of dipterans varied from 4.29 % at E1 to 29.77% at
E3 (Table IV). Difference between downstream stations (E3, E4) and stations upstream (E1, E2)
was large. Differences among sampling sites were significant (p<0.001). Values at E3 and E4
were significantly higher than those at E1 and E2. The difference between seasons was small and
not significant (p>0.05).
Diversity and biotic indices
The mean values of H’ at sampling sites ranged from 2.39 at E4 to 3.02 at E2 (Table IV). The H′
value showed significant variation among sampling sites (p<0.05); the value being significantly
higher at E2 than E1, E3 and E4. Difference between seasons was not significant (p>0.05). The
,,,
mean values of HFBI ranged from 5.38 to 8.19. The lowest value was at E1 and the highest value
was at E4 (Table IV). Differences among sampling sites were significant (p<0.05). Mean values
for wet and dry season were 6.86 and 7.17, respectively (Table IV); difference was significant
(p<0.05).
3.3. Correlations between physico-chemical parameters and macro-invertebrate metrics
9
Spearman’s correlation coefficients between physico-chemical parameters and macroinvertebrate metrics are presented in Table V. Macro-invertebrate metrics were significantly
correlated to some of the physico-chemical parameters. Dissolved oxygen was the only one
which was significantly correlated with all macro-invertebrate metrics (p < 0.05). In contrast,
neither temperature nor pH showed any significant correlations. Shannon-Wiener Diversity
Index, percent Ephemeroptera and percent Trichoptera were positively correlated to dissolved
oxygen, whereas HFBI and percent dipterans showed negative correlations. Furthermore, percent
Ephemeroptera was negatively correlated with conductivity (p<0.05)and diversity was negatively
related to TDS and conductivity.
4. Discussion
The water quality of Enfranz River downstream was rather poor compared with the upstream
region. Most likely this was mainly caused by the farmers in the downstream wetlands. Kidan
(2010) concluded that the high values of dissolved solids and conductivity in the river mouth
were primarily the result of surface run-off from agricultural lands and riverbank erosion caused
by cattle grazing and watering along the river shores.
In the present study, no measured physico-chemical parameters were significantly
different from each other between seasons. This may have been caused by the nature of the
source of the river water, i.e. the headwater springs. The volume and quality of this water did not
change significantly with seasons because the major water source is the water from the springs.
August was in the main rainy season, but October was in the post-rainy season. During this
season it was still rainy, but rainfall and runoff with sediments was less and therefore water
quality parameters were less affected. In contrast with the non-significant differences among
seasons, differences among sampling sites were often significant, but only for dissolved oxygen
content (DO) and percent oxygen saturation values we observed a clear trend along the river
from headwaters towards the inflow into Lake Tana. The DO levels in site E1 (headwaters) were
in the same range as DO levels of other small tropical forest river (Neill et al., 2006), but its
percent oxygen saturation values were on average below 70%, indicating organic pollution. The
other sites showed even lower DO values and higher reductions in percent oxygen saturation
values, particularly sites E3 and E4 showed low values. The decline in oxygen content at these
sites was most probably caused by the increased organic matter content from cattle grazing,
10
agricultural activities and fisheries (Kidan, 2010). The pH showed very little variation among
sites and values were within the permissible range for natural waters (USEPA, 2002).
The macro-invertebrate communities were dominated by the tolerant taxa Odonata,
Hemiptera and Diptera. Together they represented more than 70% of the observed individuals.
Tolerance values are based upon Hilsenhoff (1988) and Bode et al. (1996) and presented in Table
III. The tolerant Libellulidae (Odonata) were the most dominant family. Sensitive taxa as
Ephemeroptera, and Trichoptera represented together only 11.1% of the observed
numbers, whereas Plecoptera were totally lacking. The total absence of Plecoptera is in
contrast with most other studies in N.E. Africa, they are generally present in low densities and
only absent in the most degraded sites (e.g., Ndaruga et al., 2004; Sitotaw, 2006; Kibichii et
al., 2007; Kasangaki et al., 2008; Aura et al., 2010) Furthermore, the total number of
families (35) observed in the present study was rather low compared with other
studies in Ethiopia (Sitotaw, 2006) and N.E. Africa (e.g., Kibichii et al., 2007; Kasangaki et al.,
2008; Masese et al., 2009b). These results suggest that the Enfranz River along its
whole length, from headwaters until river mouth, is seriously degraded (Masese et
al., 2013).
In the headwaters the community was dominated by Hemipera and Coleoptera, followed
by Ephemeroptera (23.6%) and Trichoptera (12.3%). This is in contrast with the results of
many other studies in N.E. African rivers (e.g. Kasangaki et al., 2008; Masese et al., 2009a; Aura
et al., 2010) where the headwater stations were dominated by Ephemeropera, Trichoptera and
Plecoptera. We observed that Ephemeroptera and Trichoptera were more abundant upstream than
down-stream, especially the proportion of Baetidae (Ephemeroptera) was high upstream. This
shows that the water quality was better in the up- stream sites. However, the high abundance of
Beatitidae indicates also that the headwaters are degraded too (Masese et al., 2009a). The
Trichoptera were only present upstream, downstream they were totally lacking. This indicates a
steep gradient of water quality decrease from headwaters towards downstream.
Dipterans, dominated by Chironomidae, showed relatively high abundances in
downstream stations. Since most dipteran larvae contain hemoglobin they are able to survive low
oxygen conditions (Lake, 2003). High abundance of dipterans indicates poor water quality
(Masese et al., 2013).
11
The densities of non-insect taxa were relatively low, of the eight taxa only Physidae,
Planorbidae and Hirudinae showed a clear longitudinal gradient with higher abundances
downstream. This is not in agreement with most other studies where most non-insect taxa
increased downstream or at degraded sites (Masese et al 2009a; Raburu et al., 2009 b, Aura et al.,
2010).
Downstream stations had lower Shannon-Wiener diversity values probably due to the
presence of livestock and other anthropogenic activities. Herbivory of aquatic vegetation and
nutrient inputs via urine and fecal deposition and trampling of sediments which was a common
phenomenon in these sites (Kidan, 2010), have direct impacts on the macro-invertebrate
communities in streams (Masese et al., 2013).
Hilsenhoff Family-level Biotic Index indicates organisms’ tolerance to low dissolved
oxygen or high organic pollution. High values are indicative of organic pollution while low
values are indicative of clean water (Bode et al., 1996). We used this index to assess the water
quality over the whole river range, and observed a fair water quality only at the head water
station, but at the more downward stations water quality deteriorated to fairly poor (E2), poor
(E3) and very poor (E4), respectively.
In conclusion. Land use strongly affected oxygen concentrations, macro-invertebrate
community structure and biodiversity based on the relative abundance of the macroinvertebrate taxa. Diversity and biotic indices and percent oxygen saturation values indicated
poor and very poor water quality at the downstream stations. We conclude that the Enfranz
River downstream is severely affected by land use of the people living along the river.
5. Acknowledgements
This research was carried out under the Agriculture and Environmental Sciences College and
Fisheries, Wetlands and Wildlife Program. We are thankful for the practical and mental support
of colleagues and friends during the course of the research. The financial support from the Bahir
Dar University and Amhara Regional Agricultural Research Institute (ARARI) is highly
acknowledged. We thank Mr. Negash Atnafu for his help with the map on land-use (Fig. 1) and
12
the handling editor and two anonymous reviewers for their many constructive comments which
improved the quality of the manuscript considerably
6. References
Ambelu, A., Lock, K., Goethals, P.L.M., 2010. Comparison of modelling techniques to predict
macroinvertebrate community composition in rivers of Ethiopia. Ecological Informatics 5,
147–152.
Aura, C.M., Raburu, P.O., Herman, J., 2010. A preliminary macroinvertebrate Index of Biotic
Integrity for bioassessment of the Kipkaren and Sosiani Rivers, Nzoia River basin, Kenya.
Lakes & Reservoirs: Research & Management 15, 119–128.
Beyene, A., Addis, T., Kifle, D., Mulat, W., Kloos, H., Triest, L., 2009. Comparative study of
diatoms and macroinveretebrates as indicators of severe water pollution: Case study of the
Kebena and Akaki rivers in Addis Ababa, Ethiopia. Ecological Indicators 9, 381–392.
Bode, R.W., Novak, M.A., Abele, L.E., 1996. Quality assurance Work plan for Biological
Stream Monitoring in New York State. NYS department of Environmental Conservation,
Albany, NY.
Bouchard, R.W., 2004. Guide to aquatic macroinvertebrates of the Upper Midwest Waters. In:
Bicudo, C.E.M., T. Matsumura-Tundisi [Eds] Limnology in Brazil. ABC/SBL. Visual
Graftex Comunicação, Rio de Janeiro: pp. 365-371.
Boulton, A.J., 2003. Parallels and contrasts in the effects of drought on stream macroinvertebrate assemblages. Freshwater Biology 48, 1173-1185.
Callisto, M., Moreno, P., Barbosa, F.A.R., 2001. Habitat diversity and benthic functional trophic
groups at Serra Do Cipo, Southeast Brazi. Revue Brasilia Biology 61, 259-266.
CSA, 2007. Statistical Abstract 2007. Central Statistical Agency, Addis Ababa.
Dallas, H.F., Mosepele, B., 2007. A Preliminary Survey and Analysis of the Spatial Distribution
of Aquatic Invertebrates in the Okavango Delta. African Journal of Aquatic Science 32, 111.
Dickens, C.W.S., Graham, P.M., 2002. The South African Scoring System (SASS) Version 5
rapid bioassessment method for rivers. African Journal of Aquatic Science 27, 1-10.
13
Dudgeon, D., Arthington, A.H., Gessner, M.O., Kawabata, Z., Knowler, D.J., Leveque, C.,
Naiman, R.J., Prieur-Richard, A., Soto, D., Stiassny, M.L.J., Sullivan, C.A., 2006.
Freshwater Biodiversity: importance threats, status and conservation challenges. Biological
Reviews 81, 163-182.
Edmondson, W.T., 1959. Fresh water biology. 2nd ed., John Wiley and Sons Inc., New York,
USA.
Gooderham, J., Tysrlin, E., 2002. The water bug book. A guide to the freshwater macroinvertebrates of temperate Australia. CSIRO publishing, Australia.
Grubh, A.R., Mitsch, W.J., 2004. Distribution and abundance of macroinvertebrates in created
wetland ecosystems. In: Mitsch, W.J., Zhang, L., Tuttle, C. [Eds] Olentangy River Wetland
Research Park Annual Report 2003. The Ohio State University, Columbus, OH, pp. 105-116.
Hailu, D., Legesse, W., 1997. Assessment of pollution status of Awetu stream, Ethiopia. Bulletin
JIHS 7, 79–85.
Harrison, A.D., Hynes, H.B.N., 1988. Benthic fauna of Ethiopian mountain streams and rivers.
Archiv für Hydrobiologie Supplement 81, 1-36.
Hilsenhoff, W.L., 1988. Rapid field assessment of organic pollution with a family-level biotic
index. Journal of the North American Benthological Society 7, 65-68.
Hynes, H.B.N., Harrison, A.D., Berhe, T., 1989. Degradation of a stream crossing the city of
Addis Ababa, Ethiopia. Tropical Freshwater Biology 2, 112–120.
Jessup, B.K., Markowitz, A., Stribling, J.B., 1999. Family-level key to the stream invertebrates
of Maryland and surrounding areas. Maryland department of natural resources Chesapeake
Bay and watershed program resource assessment service monitoring and non-tidal
assessment division CBWP-MANTA-EA-99-2.
Kassahun, G., 2008. Physico-chemical and Bacteriological Drinking Water Quality Assessment
of Bahir Dar town water supply from source to yard connection (NorthWestern Ethiopia).
M.Sc Thesis, Addis Ababa University, Addis Ababa.
Kasangaki, A., Chapman, L.J., Balirwa, J., 2008. Land use and the ecology of benthic
macroinvertebrate assemblages of high-altitude rainforest streams in Uganda. Freshwater
Biology 53, 681–697.
14
Kibichii, S., Shivoga, W.A., Muchiri, M., Miller, S.N., 2007. Macroinvertebrate assemblages
along a land-use gradient in the upper River Njoro watershed of Lake Nakuru drainage
basin, Kenya. Lakes & Reservoirs: Research & Management 12, 107–117
Kidan, W.G., 2010. Biodiversity assessment: Major vegetation and land use impacts of Enfranz
Riverine wetland in Lake Tana watershed, Northern Bahir Dar, Ethiopia. MSc thesis, School
of Graduate Studies, Bahir Dar University.
Kobingi, N., Raburu, P.O., Masese, F.O., Gichuki, J., 2009. Assessment of pollution
impacts on the ecological integrity of the Kisian and Kisat rivers in Lake Victoria
drainage basin, Kenya. African Journal of Environmental Science and Technology
3, 97–107.
LaBonte, J.R., Scott, D.W., McIver, J.D., Hayes, J.L., 2001.Threatened, endangered and
sensitive insects in Eastern Oregon and Washington forests and adjacent lands. Northwest
Science 75, 185-198.
Lake, P.S., 2003. Ecological effects of perturbation by drought in flowing waters. Freshwater
Biology 48, 1161-1172.
Masese, F.O., Raburu, P.O., Muchiri, M., 2009a. A preliminary benthic macroinvertebrate index
of biotic integrity (B-IBI) for monitoring the Moiben River, Lake Victoria Basin, Kenya.
African Journal of Aquatic Science 34, 1–14.
Masese, F.O., Muchiri, M., Raburu, P.O., 2009b. Macroinvertebrate assemblages as biological
indicators of water quality in the Moiben River, Kenya. African Journal of Aquatic Science
34, 15–26.
Masese, F.O., Omukoto J.O., Nyakeya, K., 2013. Biomonitoring as a prerequisite for sustainable
water resources: a review of current status, opportunities and challenges to scaling up in East
Africa. Ecohydrology & Hydrobiology 13, 173–191.
Merrit, R.W., Cummins, K.W., 1988. An introduction to the aquatic insects of North America.
Kendall, Hunt Pub. Co., Dubuque, Iowa.
Minaya, V., McClain, M.E., Moog, O., Singer, G., Omengo, F., 2013. Scale dependent effects of
rural activities on benthic macroinvertebrates and physico-chemical characteristics in
headwater streams of the Mara River, Kenya. Ecological Indicators 32, 116–122.
15
Ndaruga, A.M., Ndiritu, G.G., Gichuki, N.N., Wamicha, W.N., 2004. Impact of water quality on
macroinvertebrates assemblages along a tropical stream in Kenya. African Journal of
Ecology 42, 208-216.
Neill, C., Deegan, L.A., Thomas, S.M., Haupert, C.L., Krusche, A.V., Ballester, V.M., Victoria,
R.L., 2006. Deforestation alters the hydraulic and biogeochemical characteristics of small
lowland Amazonian streams: Hydrological Processes 20, 2563-2580.
Raburu, P.O., Masese, F.O., Mulanda, C.A., 2009a. Macroinvertebrate Index of Biotic Integrity
(M-IBI) for monitoring rivers in the upper catchment of Lake Victoria Basin, Kenya.
Aquatic Ecosystem Health and Management 12, 197–205
Raburu, P.O., Okeyo-Owuor, J.B., Masese, F.O., 2009b. Macroinvertebrate-based Index of biotic
integrity (M-IBI) for monitoring the Nyando River, Lake Victoria Basin, Kenya. Science
Research Essay 4, 1468–1477.
Reece, F.P., Richardson, S.J., 2000. Biomonitoring with the Reference Condition Approach for
the Detection of Aquatic Ecosystems at Risk. In: Darling, L.M. [Ed.] Proceedings of a
Conference on the Biology and Management of Species and Habitats at Risk. Kamloops,
British Columbia, 15-19 February, 1999. British Columbia Ministry of Environment: Lands
and Parks, Victoria, B.C., and University College of the Cariboo, Kamloops, B.C., pp. 549552.
Shivoga, W.A., 2001. The influence of hydrology on the structure of invertebrate communities in
two streams flowing into Lake Nakuru, Kenya. Hydrobiologia 458, 121-130.
Sitotaw, B., 2006. Assessment of Benthic-Macro-invertebrate structures in relation to
environmental degradation in some Ethiopian rivers. M.Sc. Thesis, School of Graduate
studies, Addis Ababa University, Ethiopia.
Strayer, D.L., 2006. Challenges for freshwater invertebrate conservation. Journal of the North
American Benthological Society 25, 271–287.
USEPA, 2002. Summary of biological assessment programs and bio-criteria development for
states, tribes, territories, and interstate commissions: Streams and wadeable rivers. EPA 822R-02-048. Washington, D.C.: U.S. Environmental protection agency, office of
environmental information and office of water.
Vinson, M.R., Hawkins, C.P., 1998. Biodiversity of stream insects: variation at local, basin and
regional scales. Annual Review of Entomology 43, 271-193.
16
Wilhm, J.L., Dorris, T. C., 1968. Biological parameters of water quality criteria. Bioscience 18,
477-481.
17
List of Figures
Figure 1. Map of study area and land-use of Enfranz River watershed with sampling stations
E1, E2, E3, E4 and Lake Tana.
Figure 2. Relative abundance of the main taxonomic groups of macro-invertebrates at each
sampling station from August 2010 to May 2011 and the relative abundance during the wet
and the dry season.
Table I. Description of sampling sites in the Enfranz River (see also Figure 1).
Site Name
Coordinates
Altitude
Descriptions
(m a.s.l)
E1
11° 36' 2" N
1833
Head of the river, riparian vegetation with patchy
37° 16' 48" E
grasses and few shrubs. More than 10 springs join
here to create the river.
E2
11° 37' 22" N
1805
River sides surrounded by riparian vegetation.
1791
River sides surrounded by big trees, 3-4 m high
37° 17' 23" E
E3
11° 38' 23" N
37° 17' 58" E
with many branches. Used by local people to
cultivate crops and for washing and bathing site.
E4
11° 38' 51" N
1789
Mouth of the river. Agriculture, cattle grazing and
fisheries dominate.
37° 18' 39" E
18
Table II. Mean ± SE values of physico-chemical parameters per site and season along the
Enfranz River (2010-2011). DO is given as absolute amount (mg l-1) and as saturation value at
ambient temperature (%). Different letters within the same column show significant differences
(p < 0.05). SE = Standard error.
Parameters
DO (mg l-1)
DO (%)
Temp (oC)
TDS (ppm)
Cond (μS cm-1)
pH
Sampling sites
E1
6.08±0.14a
67.43+2.37
20.33±0.62a
94.75±15.77ab
207.18±9.09ab
7.12±0.02a
E2
5.16±0.07b
58.16+1.80
21.12±0.97a
82.78±10.51bc
165.50±21.04bc
7.16±0.03a
E3
4.19±0.12c
45.23+1.35
19.17±0.50a
96.70±3.05bc
192.03±7.46ac
7.16±0.01a
E4
3.27±0.23d
37.30+2.53
21.88±0.25a
146.50±20.04ad
246.75±17.81ad
7.14±0.01a
Sampling season
Wet
4.66±0.45a
51.51+7.49
19.98±0.66a
92.45±11.41a
192.04±16.26a
7.14±0.03a
Dry
4.69a±0.39a
52.56+5.28
21.26±0.36a
117.91±12.62a
213.69±11.89a
7.15±0.01a
19
Table III. Total number of collected macro-invertebrates per family at each sampling site and per
season in the Enfranz River (2010-2011). Assigned tolerance values range from 0 to 10 for
families and increase as water quality decreases.
Sampling sites and seasons
Family
Tolerance value
E1
E2
E3
E4
Wet
Dry
Total
Baetidae
5
329
243
66
0
305
327
632
Caenidae
6
205
106
63
7
171
210
381
Heptageniidae
4
76
0
0
0
28
48
76
Potomanthidae
3
25
0
0
0
7
18
25
Hydropsychidae
4
166
101
0
0
152
115
267
Hydroptilidae
4
55
0
0
0
33
22
55
Philoptotamidae
3
34
0
0
0
29
5
34
Phryganeidae
4
67
0
0
0
52
15
67
Rhyacophilidae
-
10
0
0
0
9
1
10
Aeshnidae
3
83
49
0
0
88
44
132
Coenagrionidae
9
12
77
381
636
426
686
1106
Libellulidae
9
17
60
503
1960
888
1652
2540
Calopterygidae
5
26
0
0
0
6
20
26
Belostomatidae
9
150
288
124
573
451
684
1135
Corixidae
8
57
122
211
285
271
404
675
Gerridae
6
189
350
47
64
276
374
650
Naucoridae
8
81
102
57
0
107
133
240
Nepidae
7
74
133
55
0
104
158
262
Notonectidae
9
43
65
143
319
229
341
570
Pleidae
8
0
69
57
78
96
108
204
Ephemeroptera
Trichoptera
Odonata
Hemiptera
20
Veliidae
7
63
113
66
61
127
176
303
Dytiscidae
5
121
85
0
0
77
129
206
Elmidae
4
295
84
78
0
216
241
457
Gyrinidae
4
227
87
80
123
285
232
517
Haliplidae
5
67
65
65
58
123
132
255
Hydrophilidae
5
70
71
53
66
124
136
260
Ceratopogonidae
6
25
116
175
345
289
372
661
Chironomidae
8
66
255
595
831
743
1004
1747
Culicidae
8
28
21
198
431
255
423
678
Physidae
8
0
71
0
180
135
116
251
Planorbidae
7
0
0
69
180
95
154
249
Lymnaeidae
6
0
9
0
0
4
5
9
Sphaeriidae
8
0
37
0
0
37
37
37
Pisauridae
8
0
63
71
146
114
166
280
Tetragnatidae
4
15
61
0
51
60
67
127
Hydracarina
6
14
34
0
19
60
7
67
Hirudinea
10
0
0
35
60
40
55
95
2690
2909
3192
6473
6512
8774
15286
Coleoptera
Diptera
Mollusca
Arachnida
Total Individuals
21
Table IV. Mean + 1 SE of macro-invertebrate metrics per site and season in the Enfranz River (20102011). H′ = Shannon-Wiener Diversity Index, HFBI = Hilsenhoff Family-level Biotic Index. Different
letters within the same column show significant differences (p < 0.05). Abbreviations used: SE =
Standard error, NO = No individuals observed; Ephem = Ephemeroptera, Trichop = Trichoptera.
H′
HFBI
% Ephem
% Trichop
% Diptera
E1
2.97±0.033a 5.38±0.14a 23.59±0.46a 12.59±2.8a 4.29±1.58a
E2
3.02±0.031a 6.61±0.11b 11.92±0.58b 3.60±0.5b
13.24±1.44b
E3
2.70±0.026b 7.78±0.03c 3.84±0.24c
NO
29.77±1.15c
E4
2.39±0.65c
8.19±0.08d 0.12±0.12d
NO
25.57±2.16c
Wet 2.80±0.08a
6.86±0.44a 9.84±3.39a
5.39±2.68a 17.59±4.40a
Dry
7.13±0.39b 9.89±3.43a
2.70±1.29b 18.85±3.44a
2.74±0.11a
22
Table V. Spearman’s rank correlation coefficients between physico-chemical parameters and
macro-invertebrate metrics (N = 16). H′ = Shannon-Wiener Diversity Index, HFBI = Hilsenhoff
Family-level Biotic Index. Abbreviations used: Ephem = Ephemeroptera, Trichop = Trichoptera.
Metrics
H′
HFBI
%Ephem
% Trichop
% Diptera
Physico-chemical
R
p-value
parameters
Dissolved oxygen
0.80 < 0.001
Temperature
-0.20 0.231
TDS
-0.56 0.012
Conductivity
-0.56 0.011
pH
-0.09 0.374
Dissolved oxygen
-0.95 < 0.001
Temperature
-0.19 0.236
TDS
0.46 0.038
Conductivity
0.37 0.079
pH
0.16 0.281
Dissolved oxygen
0.95 < 0.001
Temperature
-0.16 0.276
TDS
-0.41 0.057
Conductivity
-0.56 0.011
pH
0.09 0.374
Dissolved oxygen
0.91 < 0.001
Temperature
0.29 0.141
TDS
-0.31 0.123
Conductivity
-0.20 0.226
pH
-0.20 0.229
Dissolved oxygen
-0.83 < 0.001
Temperature
-0.29 0.139
TDS
0.21 0.220
Conductivity
0.09 0.373
pH
0.21 0.221
23
Figure 1. Map of study area and land-use of Enfranz River watershed with sampling stations
E1, E2, E3, E4 and Lake Tana.
24
Figure 2. Relative abundance of the main taxonomic groups of macro-invertebrates at each
sampling station from August 2010 to May 2011 and the relative abundance during the wet
and the dry season.
25